Novel Signal Detectors for Ambient Backscatter Communications in Internet of Things Applications

Chen, Yunfei; Feng, Wei

Abstract

Ambient backscatter communication enables lowcost low-rate wireless interconnections for Internet of Things (IoT) applications. In this work, new signal detectors for different cases of ambient backscatter communications are derived. Specifically, both coherent and partially coherent detectors are obtained for Gaussian ambient signals and phase shift keying (PSK) ambient signals. Maximum likelihood detection method and improved energy detection method (including energy detection and magnitude detection as special cases) are adopted. Numerical results show that the energy detection method has the best performance when the ambient signals are Gaussian, while the magnitude detection method has the best performance when the ambient signals are PSK modulated. Both are comparable to the optimum maximum likelihood detection. Numerical results also show that the improved energy detection method is very flexible and that detectors for PSK ambient signals are slightly better than those for Gaussian ambient signals.

Citation

Chen, Y., & Feng, W. (2023). Novel Signal Detectors for Ambient Backscatter Communications in Internet of Things Applications. IEEE Internet of Things Journal, https://doi.org/10.1109/JIOT.2023.3305645

• Journal Article Type: Article
• Acceptance Date: Aug 11, 2023
• Online Publication Date: Aug 16, 2023
• Publication Date: 2023
• Deposit Date: Aug 30, 2023
• Publicly Available Date: Aug 30, 2023
• Journal: IEEE Internet of Things Journal
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/JIOT.2023.3305645
• Public URL: https://durham-repository.worktribe.com/output/1726451
• Publisher URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6488907